Transcript Slide 1

U. S. Bureau of Labor Statistics
Do Poor Pay More, Store by
Store?
Greg Kurtzon
Robert McClelland
Preliminary and Incomplete
We thank Aylin Kumcu for her assistance with this research. All errors are our own. All views expressed in this paper
are those of the authors and do not necessarily reflect the views or policies of the U.S. Bureau of Labor Statistics.
Do people with different incomes face different
prices?
• The poor pay more because they
– are less mobile
– shop at small, independent stores (not chains, not club stores)
– shop in areas with higher insurance and security costs
• The poor pay less because they
–
–
–
–
have a lower opportunity cost of time
buy lower quality products
shop in areas with lower wages
shop in outlets with fewer amenities
2
Real income distributions
Some analyses conclude that the distribution of income has
been widening
The ‘real’ income distribution may not be as wide, or may
be wider, than the ‘nominal’ distribution suggests
3
Previous literature
• Caplovitz (1963) “The Poor Pay More”
• BLS (1965)
– independent stores, patronized by low income families, charge
more
• Summary in Sexton (1971)
– no difference, or poor pay more
• Summary in in Kaufman, et. Al., (1997)
– no difference, or poor pay more
• Hayes (2000)
• Aguiar and Hurst (2005)
4
Previous literature
Hayes (2000) uses BLS 1998 micro-data for six
homogeneous goods, and finds that prices for a set of
homogeneous items sold in ‘poor’ areas are up to 6%
lower. ‘Poor’ is defined by characteristics at the zip code
and county level
Aguiar and Hurst (2005) use AC Nielsen ‘Homescan’ data
for Denver 1993-5. 85% of purchases come from four
chains. They conclude that poor pay about 5% less
5
Data
• We use the telephone point of purchase survey (TPOPS)
to determine how much households with different
incomes spend at specific outlets
• That information, combined with price data is used to
construct average prices levels for different incomes
• We don’t have data on the purchasing patterns of
different households within an outlet
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TPOPS
• Quarterly survey of around 15,000 consumer units,
contacted randomly by phone
• Respondents are asked for recent (recall period varies
by good) dollar expenditures on one of 16 POPS groups
for each outlet shopped at
– One POPS group asked for each PSU each quarter
– Full rotation every 4 years
– One consumer unit intended to stay in for 4 quarters
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TPOPS
In 2001 only, respondents were asked to place their consumer
unit in one of three income groups:
– 1 Lower
less than $8,000 for CUSIZE < 2; less than $18,000 for CUSIZE = 2;
less than $18,000 for CUSIZE = 3; less than $24,000 for CUSIZE > 3
– 2 Middle
$8,000-$30,000 for CUSIZE < 2; $18,000-$57,000 for CUSIZE = 2;
$18,000-$64,000 for CUSIZE = 3; $24,000-$66,000 for CUSIZE > 3
– 3 Upper
greater than $30,000 for CUSIZE < 2; greater than $57,000 for CUSIZE = 2;
greater than $64,000 for CUSIZE = 3; greater than $66,000 for CUSIZE > 3
About 15% group 1, 50% group 2, 35% group 3
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TPOPS
• Only first time interviewees were asked the question,
with around an 80% response rate
• Therefore, an income group can be assigned to at least
some respondents in quarters 2001 Q1 – 2002 Q3
• The quarter with the most respondents with an assigned income
group is 2001 Q4, about 55%
• The attrition rate is around 17% per quarter, could be a bit high
• Replacements are not asked income question
• Outlet income group weights
– For each outlet in the 2001 Q1 – 2002 Q3 TPOPS sample, total
expenditures for each income group were calculated
– Many outlets have only one or two consumer units shopping there
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Weights
• The probability of selecting a store should be proportional
to expenditures in that store (PPS)
• The probability of selecting an item should be
proportional to the expenditures on that item
• Expenditures in outlet o by income group I
eo, I

eo
E 1it   prt i  
 I
 eo  eo, I
o
o I
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Weights
We create an adjustment factor AoI to reflect expenditures
by specific income groups
E(i 1it Ao,I pit )  i E(1it )AoI pit
eo , I
eo

i  eo
o
 eo , I
o
 I eo , I
o  I e o , I
pit  i
eo , I
o e o , I
pit
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Commodities
• Prices from Aug 2002 – April 2007
• Missing prices and weights are deleted
• Each observation is a price quote for each income group
that used that outlet
• More than one income group can shop at a given outlet
• 27 food items, plus gasoline
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Estimation strategy
• We can directly compare average prices paid by low
income CUs to middle and high income CUs
• Equivalently, we can regress log(price) on dummy
variables for middle income and high income CUs
• To account for inflation and interarea variation, we add
dummy variables for time period and area
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Two methods to account for quality variation
1.
Identify very specific, homogeneous items, then
estimate
log pit  H DH  M DM  t t Dt  a a Da  it
2.
Create dummy variables for price determining
characteristics, then estimate
log pit  H DH  M DM  t t Dt  a a Da  s s Ds  it
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Apple Checklist
BUREAU OF LABOR STATISTICS
U.S. DEPARTMENT OF LABOR
CONSUMER PRICE INDEX - ELI CHECKLIST
collection
outlet
quote
arranging
period: __ __ __ __
number: __ __ __ __ __ __ __ code: __ __ __ code:
__ __ __ __
_________________________________________________________________________________________
ELI No./
cluster
title
FK011 APPLES
code
01A
item availability:
1-AVAILABLE
2-ELI NOT SOLD
3-INIT INCOMPLETE
purpose of checklist: 1-INIT
2-INIT COMPL 3-SPEC CORR
4-SUB
5-REINIT
6-CHECK REV
_________________________________________________________________________________________
CURRENT PERIOD
| SALES TAX
|
price: _ _ _ _ _ _ . _ _ _
|
included:
YES
NO
|
type of price: REG
SALE
|
|
quantity: __ __ __
|
|
size: _ _ _ _ . _ _ _
pair: YES
NO
|
|
unit of size: ______________
|
|
|
|
|
YEAR-ROUND | in-season: JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
____________|____________________________________________________________________________
respondent:
location:
_________________________________________________________________________________________
field message:
_________________________________________________________________________________________
VARIETY
A1 Baldwin
A2 Ben Davis
A3 Delicious
** B1 Red Delicious
** B2 Golden Delicious
A4 Fuji
A5 Gala
A6 Granny Smith
A7 Gravenstein
A8 Grimes Golden
A9 Jonathan
A10 McIntosh
A11 Rome Beauty (Red Rome)
A12 Stayman
A13 Winesap
A14 York (York Imperial)
A15 Not known
A99 Other,
______________________________
ORGANIC CERTIFICATION
C1 Not USDA certified organic
C2 USDA certified organic
C3 Other organic claim
** WEIGHT
(See metric sizes, FK011 page 2 of 2)
G1 0-10 pounds (0-4.5 Kg)
G2 Above 10 pounds (Above 4.5 Kg)
** PACKAGING
H1 Loose
H2 Multi-pack
H3 Single item, individually
packaged
** SIZE REPRESENTS
I1 Weight labeled
I2 Weighed one multi-pack
(QUANTITY = # of packages priced)
I3 Weighed 2 apples, entered YES for PAIR
(QUANTITY = # of apples priced)
** OTHER ITEM IDENTIFIERS
J99
______________________________
K99
______________________________
OTHER FEATURES
D99 _____________________________
E99 _____________________________
** GRADE
F1 U.S. Extra Fancy
F2 Other grade/grade not available
ZZ99
________________________________________________________________________________________
BLS 3400B (Rev. February 1995)
FK011 page 1 of 2
Revised January 2002
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Examples of homogeneous items
• National brand white bread, regular, not buttertop/salt
free/dietetic/etc, not frozen, pre-pkged, 24oz
• National brand, chicken half breasts, skinless, fresh, no
seasoning
• National brand iceberg lettuce, single item package
• National brand bacon, reg slice, not low salt, not
smoked, not maple flavored or brown sugar cured
• National brand bleached white all-purpose flour 5 lb
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Table 5:
Total Number of Significant Coefficients and
their Sign, by Regression
Outlets/regression
All outlets
Homogeneous items
Characteristic Vars
Medium
+
-
High
+
-
4
10
9
8
5
6
7
7
Positive coefficients indicate that CUs in the income group
pays more than low income CUs
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Table 5:
Total Number of Significant Coefficients and
their Sign, by Regression
Outlets/regression
All outlets
Homogeneous items
Characteristic Vars
Medium
+
-
High
+
-
4
10
7
7
9
8
5
6
5
9
5
7
9
10
2
2
Club stores Omitted
Homogeneous items
Characteristic Vars
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